Table of Contents
In this interview, we sit down with Alejandro in Playa del Carmen, Mexico, to dig into the real day-to-day of a working trader—how he frames confidence, why statistics beat feelings, and how automation supports discretionary decisions. Alejandro isn’t selling fairy tales; he’s a practitioner who journals hard, backtests deeply, and coaches others through the messy middle between ideas and execution. If you’ve ever felt stuck chasing “confidence” before placing a trade, his reframing—curiosity first, results second—will hit home.
You’ll learn how Alejandro turns stats into conviction, builds process-based daily goals, and calibrates stops and targets so they reflect real volatility—not hope. We cover the win-rate vs. reward-to-risk trade-off, why journaling kills hindsight bias, and where simple automation (alerts, assistants, or EAs) saves hours while improving discipline. By the end, you’ll have a clean blueprint to test, execute, and adapt a strategy you can actually run—without over-tweaking it every time the market wiggles.
Alejandro Playbook & Strategy: How He Actually Trades
Core philosophy: curiosity beats confidence
Confidence comes after reps. Alejandro starts from curiosity, and so he can execute without obsessing over outcomes, then adapts based on what the data shows. This mindset keeps him from freezing or forcing trades when uncertainty spikes.
- Treat every trade as a data point; aim to learn first, profit second.
- Detach from individual results; judge yourself on process completion, not P&L.
- After each session, list one thing to keep and one thing to tweak—then test, don’t guess.
Separate CEO work (strategy) from factory work (execution)
He splits trading into two jobs: long-horizon strategy design and daily execution. You don’t rebuild the engine mid-drive; you run the line, log defects, and schedule changes when the data says so.
- Schedule weekly “CEO blocks” to review stats and plan tweaks; never tweak intraday.
- Write a premarket execution checklist; if a step fails, stand down until it passes.
- Log every deviation from plan and treat it like a process flaw to be fixed in CEO time.
Risk sizing that survives real life
Expectancy matters, but the path (wins/losses) must fit your psychology and trade frequency. Alejandro adjusts risk so drawdowns stay tolerable and execution stays consistent.
- Day traders: cap risk at ≤0.5% per trade; frequent entries compound intraday drawdowns.
- Swing traders: 1% per trade is a common ceiling if stats and psychology allow.
- Choose your win-rate/R: R mix intentionally (e.g., 60% at 1:1 vs. 30% at 3:1); both can work—pick the path you’ll actually execute.
Entries, stops, and exits you’ll actually follow.w
He refined stops, targets, and management rules by testing—not vibes. For him, auto-moving to breakeven killed edge; partials plus realistic targets worked better. Your exact settings should come from tests, then be enforced by routine.
- Define stops from structure/volatility, not money you “wish” to risk.
- Avoid automatic BE moves if testing shows it truncates winners; protect with structure instead.
- Pre-commit to partials (e.g., scale at 1R or first target) and a final take-profit; no on-the-fly decisions.
One strategy, many contexts
He can run a single-core strategy across multiple market contexts by clarifying when it thrives and when it stands down. Think of strategies like employees—each has a role and environment where it performs best.
- Tag every trade with the market context (trend, range, volatility regime); only deploy where stats are positive.
- Keep a “do-not-trade” list of contexts that flip your edge negative.
- If you want diversification, run the same ruleset in two distinct contexts rather than inventing five new systems.
Backtesting, journaling, and real patience
Backtests are for ranking ideas and setting expectations—not for guaranteeing profits. Most tests won’t pan out; that’s normal. Pair testing with journaling to catch the psychology that stats alone miss.
- Expect most backtests to disappoint; iterate quickly and document why.
- Journal process metrics daily (setup quality, rule adherence, reaction to losses), not just P&L.
- Only promote tweaks from journal → sandbox → live after a minimum sample (e.g., 30 trades).
Daily routine: run the line, don’t redesign it
Execution days are about manufacturing clean reps, not rewriting playbooks. Treat your trading like a plant: open the line, run the checklist, and ship consistent product.
- Premarket: context scan, levels, scenarios, risk caps, alerts set—then trade the plan.
- Intraday: no strategy edits; only execute, record, and protect risk.
- Postmarket: grade adherence, tag mistakes, queue potential tweaks for CEO time.
Adaptation when life changes
When circumstances change (travel, schedule, energy), he adjusts frequency or management rules instead of forcing the old cadence. Strategy fit includes lifestyle fit—protect that or consistency dies.
- If you start missing trades, reduce markets/timeframes or switch to alerts + fewer high-quality sessions.
- Re-validate stops/targets after any major routine change before sizing up again.
- Keep risk lower for two weeks after schedule shifts; only scale when adherence is back above 90%.
Size risk to survive drawdowns; keep position small and consistent
Alejandro is blunt about this: your edge dies the moment your position size gets emotional. He frames risk as the only lever you fully control, so he sizes down until losing streaks barely dent confidence. That way, when variance slaps you, you’re still calm enough to execute the next setup. The goal isn’t to swing bigger; it’s to stay in the game long enough for the math to work.
He keeps a fixed-per-trade risk so the account’s P&L path stays predictable and stress stays low. If volatility spikes, Alejandro adjusts stop distance but keeps risk constant, letting size float to match market conditions. He also caps daily drawdown so the worst day never becomes a spiral, then returns tomorrow like nothing happened. Small and consistent sizing isn’t timid—it’s the backbone that lets a real strategy compound.
Use volatility to set stops, targets, and daily risk caps.
Alejandro builds his entire protective shell around volatility so the market’s noise doesn’t kick him out or lull him into lazy risk. He sets stops using structure plus a volatility buffer—think average true range (ATR) multiples—so random wiggles don’t tag him. When volatility expands, he widens the stop and cuts position size to keep dollars-at-risk constant. Targets scale the same way: if the range grows, he lets winners breathe; if it contracts, he banks sooner.
He also sets a daily risk cap tied to current volatility so one wild session can’t wreck the week. If ATR is surging, he plans fewer, higher-quality trades; if it’s shrinking, he tightens expectations and avoids forcing moves. Volatility isn’t just a stat for Alejandro—it’s the thermostat for his stops, targets, and how hard he presses the gas each day.
Diversify by setup, timeframe, and market; same mechanics, different context.s
Alejandro keeps the playbook simple but uses it across multiple contexts to smooth the equity curve. He runs the same mechanics—entry trigger, stop logic, partials, and exit—on more than one setup and time frame, so no single market condition dictates his month. If trending indices go cold, a mean-reversion pair or a range-bound FX cross can still produce clean reps. The point isn’t more strategies; it’s one set of rules proven in several places.
He limits correlation by mixing instruments and session windows, not by adding random tactics. Alejandro tags each trade by context (trend, range, volatility regime) and only deploys where stats are positive for that ruleset. If two markets move together, he caps total exposure so a single theme can’t double-hit his risk. Same mechanics, different lanes—diversification that a solo trader can actually execute.
Trade mechanics over predictions; execute the checklist, ignore opinions
Alejandro treats predictions as entertainment and mechanics as the job. He starts every session with a prewritten checklist that defines setup quality, risk, and management rules—then he just follows it. If the chart doesn’t meet the criteria, he passes without debate. No guru calls, no news hype, no “I feel like it’s due.”
During the trade, Alejandro manages by rules: protect structure, trigger partials, and move to the final target or exit—nothing ad-hoc. If he catches himself rationalizing, he closes the platform and resets rather than “fixing” the market. He grades each trade on rule adherence, not on P&L, so good losses and bad wins are obvious. That’s how his performance stays consistent when opinions get loud.
Define exit rules before entry: partials, reloads, and walk-away points.
Alejandro decides his exit before he clicks buy or sell, so he isn’t negotiating with the market mid-trade. He maps a first partial at a logical milestone—often around 1R or the first opposing structure—to bank progress and reduce pressure. The final target is anchored to context and volatility, so he’s not cutting winners just because the P&L looks “big.” If price invalidates the setup structure, he’s out immediately—no hoping for a bounce.
He also predefines when to reload and when to walk away. Reloads require a fresh signal after a partial or stop-out, not revenge entries; the risk reset, and the thesis must still be valid. Walk-away points cap the number of attempts per setup or per session, so one idea doesn’t drain the day. By locking exits in advance, Alejandro protects expectancy, keeps emotions quiet, and lets the strategy—not impulse—decide how a trade ends.
Alejandro’s interview boils down to one thing: build a trading life you can actually run every day. He swaps “confidence” for curiosity so execution doesn’t hinge on mood, and he judges himself on process, not P&L. That starts with fixed risk per trade, daily drawdown limits, and stops placed by structure and current volatility—not by wishful thinking. When volatility expands, he widens stops and shrinks size to keep dollars-at-risk constant. Before he ever clicks, exits are scripted: partials at logical milestones, invalidation on structure breaks, and a final target that fits the day’s range. Nothing ad-hoc, no negotiating with the market mid-trade.
From there, Alejandro separates “CEO time” (design and testing) from “factory time” (pure execution). He journals relentlessly, tagging context—trend, consolidation, volatility regime—so he knows where his ruleset actually wins. The same mechanics run across multiple setups, timeframes, and markets to smooth the curve without multiplying complexity. Light automation helps—alerts, routines, even simple assistants—but it never replaces rule-based judgment. And when life changes, he adapts the cadence before he torches discipline: fewer sessions, tighter focus, lower risk until adherence is back above 90%. If you take one page from Alejandro’s playbook, make it this: protect the process so your edge can show up, trade after trade, month after month.
